Opposition theory and computational semiotics
Opposition theory suggests that binary oppositions (e.g., high vs. low) underlie basic cognitive and linguistic processes. However, opposition theory has never been implemented in a computational cognitive-semiotics model. In this paper, we present a simple model of metaphor identification that reli...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
University of Tartu Press
2015-11-01
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| Series: | Sign Systems Studies |
| Subjects: | |
| Online Access: | https://ojs.utlib.ee/index.php/sss/article/view/15880 |
| Summary: | Opposition theory suggests that binary oppositions (e.g., high vs. low) underlie basic cognitive and linguistic processes. However, opposition theory has never been implemented in a computational cognitive-semiotics model. In this paper, we present a simple model of metaphor identification that relies on opposition theory. An algorithm instantiating the model has been tested on a data set of 100 phrases comprising adjective-noun pairs in which approximately a half represent metaphorical language-use (e.g., dark thoughts) and the rest literal language-use (e.g., dark hair). The algorithm achieved 89% accuracy in metaphor identification and illustrates the relevance of opposition theory for modelling metaphor processing. |
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| ISSN: | 1406-4243 1736-7409 |